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Bayesian analysis of panel data using an MTAR model

  • Yoon Young Jung
  • Dong Wan Shin
  • Man-Suk Oh
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    Bayesian analysis of panel data using a class of momentum threshold autoregressive (MTAR) models is considered. Posterior estimation of parameters of the MTAR models is done by using a simple Markov Chain Monte Carlo (MCMC) algorithm. Selection of appropriate differenced variables, test for asymmetry and unit roots are recast as model selections and a simple way of computing posterior probabilities of the candidate models is proposed. The proposed method is applied to the yearly unemployment rates of 51 US states and the results show strong evidence of stationarity and asymmetry.

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    Article provided by Taylor & Francis Journals in its journal Journal of Applied Statistics.

    Volume (Year): 32 (2005)
    Issue (Month): 8 ()
    Pages: 841-854

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    Handle: RePEc:taf:japsta:v:32:y:2005:i:8:p:841-854
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    1. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    2. Enders, Walter & Granger, Clive W J, 1998. "Unit-Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 304-11, July.
    3. Mehmet Caner & Bruce E. Hansen, 1998. "Threshold Autoregressions with a Near Unit Root," Working Papers 9821, Department of Economics, Bilkent University.
    4. Gary Koop & Simon M. Potter, 1998. "Dynamic asymmetries in US unemployment," ESE Discussion Papers 15, Edinburgh School of Economics, University of Edinburgh.
    5. Bruce E. Hansen, 1997. "Threshold effects in non-dynamic panels: Estimation, testing and inference," Boston College Working Papers in Economics 365, Boston College Department of Economics.
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